Mobley vs Workday

AI Legislation and Its Impact on HR Technology: Insights from Mobley vs. Workday Case

In this episode, Andrew Gadomski and Jason Roberts return to discuss the latest developments in recruiting technology with a focus on the Mobley vs. Workday lawsuit. They delve into the implications of recent AI-related legislation on HR tech companies and the broader industry. The hosts provide a detailed overview of the case where plaintiffs allege Workday's AI systems facilitated age and disability discrimination in their automated job application processes. With the judge allowing the case to proceed as a collective action, the conversation shifts to the effects this ruling could have on HR technology, including HCM tools, applicant tracking systems, and CRM systems. They explore the potential winners and losers in this scenario, emphasize the importance of AI audits, and discuss the practicality of Workday notifying a vast number of applicants about the case. Additionally, Jason shares insights about his latest venture, Better Thing AI, and its compliance with AI legislation.

00:00 Introduction and Hosts
00:32 AI Legislation and Lawsuit Overview
01:09 Details of the Workday Lawsuit
02:37 Notification Challenges and Solutions
09:59 Merits of the Case and AI Concerns
13:15 Implications for HR Technology
19:55 The Impact of Class Action Suits
20:59 Potential Winners and Losers
23:05 Automation in Recruiting
23:41 AI Legislation and Job Matching
24:36 Risks and Responsibilities in AI Deployment
28:41 Challenges in Automated Employment Decisions
32:32 Concluding Thoughts on AI in HR Tech

Transcript

Jason: 0:00

Hey everybody. I'm

Andrew: 0:00

Andrew Gadomski. And I'm Jason Roberts. And this is recruiting technology, the best in bots, automation, and all things algorithmic anyway on the internet every once in a while.

Jason: 0:12

Every once in a while. That's right. Every once in a while. This time is like two years, I think. Like two years.

Andrew: 0:18

Yeah. It's been a minute. We talk every week like this, but we decided to record it.

Jason: 0:23

Yeah. Well, before it was such a production. Now we're just not gonna do the production. We'll just have our normal hangout and you guys can join on along. And today we actually have a topic because something came up in the socials, on the medias that came to our attention. Andrew has, in the time since we last spoken to you, fine folks. We've had a bunch of legislation related to AI come up. He is become the resident expert in this thing and companies will engage he and his consulting business to perform their AI audits. And of course there was some big AI lawsuit news that came out this past Friday. And Andrew, you wanna tell us what that's all about?

Andrew: 1:08

Thanks, Jason. And yeah I gotta tell you, it's there's a lot going on in the last two and a half weeks in the world of hr. So, so really what we've got here, and this has been going on a while, is there were four plaintiffs the initial one gentleman Mobley, who took on an action against Workday in federal court in the northern district. Of California's federal court, and this is a longstanding lawsuit back and forth. Lots of briefs, lots of changes. And ultimately the judge the Honorable Rita Lin, I believe it is, that's without me looking. She went ahead and granted the plaintiff. The ability to have this case go to collective action. So the plaintiffs have said we've applied to a number of jobs through Workday systems at various companies, and we have. We have done it at all hours of the day. We have received automated responses at all hours of the day, and in some of them very fast. And our contention is that Workday is facilitating discrimination based on our age. And as individuals with disability. So that was the claimant, right? That's the, so this goes back and forth between Workday and the plaintiffs for a while, like I said, and it slowly makes itself to where we were, this not Friday, but the previous Friday, which is, judge Lin says, yeah, there's enough here where Workday, you gotta notify everybody who's applied since September of 2020 that they can go ahead and be notified of this case and become a plaintiff. And that's not a little thing. There's the Workday went ahead and said, this is really, this is very, this is a very large number of applicants. They estimated 1.1 billion with a B and said, you know, this is undue burden. And the, you know, in, in a very it almost like in a New Jersey way, it was the ruling basically said tough. The number of the counts of the actions or the number of the potential plaintiffs doesn't dismiss the fact that they would get notice. And so the plaintiffs and defense are supposed to coordinate over the next few weeks to figure out how they are going to do this. How are they gonna execute notification and. Jason, as you saw when I saw this, it's like, well, there's gonna be plenty of blogs and plenty of people coming out saying, oh my gosh, you know, the sky is falling and this is what the case is about. And this is not new stuff. My position was, okay, well they're gonna have to do it anyway here. Here's the way that I believe. So I wrote an article that said, here's the way that Workday should do this. Here's how they should notify. All these individuals, and here's, and I said, I don't at this point, talking about what the case is about doesn't mean anything. Like they have to do it. So that's what my article came up and I feel, well, that's the starting

Jason: 4:46

point. It's the starting point is they've

Andrew: 4:48

gotta notify these people. They gotta notify, you know, they say 1.1 billion. I'm not convinced that those, you know, I think there's some up in the air.

Jason: 4:57

That came from, there's probably 1.1 billion applications. Yeah, probably not 1.1 billion individuals.

Andrew: 5:04

Right. So that's what they said. There's 1.1 applications. They don't, they didn't give any numbers related to unique applicants, but every time someone, so if someone was to apply to multiple jobs at one company. They have say you, I apply to you know, what's on my west, you know, Samsung and I Go ahead. I apply, I don't know if they're a Workday customer, by the way. I'm just on a Samsung phone. I applied to seven jobs. Well, that was seven transactional opportunities where. The system put me through some the organization had to put me through some assessment, right? So I applied seven times there, but then I went to Apple and let's just say they're on Workday and I applied seven times there. Well, now there's 14 potential counts. There's 14 submissions to two companies. Yeah. And so I think that, I understand why Workday is like, you gotta be kidding me. At the same time, they're like, well, this is insurmountable. And my article that I feel all cool'cause like my article got like 10,000 impressions. Like I don't think I've ever had something like that happen. And it's like, okay, it's not impossible, it's just okay, you have to do it. And. My position has been, stop, shareholders get announced, all kinds of stuff on proxy votes. A mutual fund changes over and they let hundreds of thousands of people, if not millions of people know, and companies like Morgan Stanley do this stuff every day. I'm like, don't tell me that. Workday can't, if. If they can't figure out who's applied the jobs at their customers in a four year period, I have a lot of questions about whether or not their a, their new AI suite is worth its name. Right. You gotta be able to at least know who applied using your data stores. But that's, well,

Jason: 7:01

They, that's the. No matter what, if you're dealing with a billion records of anything, it is difficult. It's difficult to dedupe a billion records. It's difficult to send a billion emails. Oh, yeah. It's difficult to, like, I don't care if you're on SendGrid or what, but like my plan doesn't have a billion in it. Like I can't send the plan I have for sending out massive amounts of email and I have, I've got one. I don't even it's a scale that I haven't even considered before. And the cost of that is so significant.

Andrew: 7:35

It's tremendous. And yeah it is. You know, the little Diddy that I wrote said, you know, you gotta let your, you know, all Workday customers need to know what's going on, you. Work with the Workday customers so they could work with their applicants on notification. There's,

Jason: 7:53

you know, recommend place some burden. There's nothing worse than, Hey customers, I'm being sued. By the way, you might also be at risk. Can you please take this legal action for me? Like, that seems like a loser.

Andrew: 8:08

The judge hasn't necessarily said you have to do it a certain way. So it is on Workday to figure out what are they gonna do to reduce their risk associated, with the action itself. You know of, excuse me, the transactions of a, of a. Applications.

Jason: 8:25

Yeah.

Andrew: 8:25

But, okay do you wanna call all your customers and let them know, Hey, I need you to notify them, or then there's the GDPR problem.

Jason: 8:34

Right. And see even if Workday's, so if Workday's customers have to do the notifications for big customer, so for like a, I don't know. Well, JP Morgan's on. Oracle. They, Oracle will be incapable of doing this by the way. They, it's just functionally impossible, that technology, right. But but yeah. So say Microsoft is on Workday, I don't know who is right. So say Microsoft is on Workday, they literally have millions of applicants. So them to send out a notification to millions of applicants is still a giant PIA for them. Oh,

Andrew: 9:11

It is, it's tremendous. And one of the things I noted is, okay, you can break it up. And I, you know, I suggested that Workday should lean on every single one of its ecosystem partners. So like, if you're, yeah. If you have an integration with Workday, like your paradox or your phenom. If I was workdays chief counsel, I would say we're gonna sweat that asset as much as possible because we're giving them a bunch of business. Right. Yeah,

9:39

I think you would.

Jason: 9:40

I can see that. Well also, you know, they do have, I mean, surely they all have, comms sending partnerships, they've gotta have, oh, I mean, I, my contracts don't have billions. I'm sure that theirs have billions of transactions for for email messages. Right. So I guess they could do that. But anyway, it's it's egregious, but beyond the, what they need to send, let's talk about the merits of the case. Okay. Merits of the case. Seemed like a total steaming pile of garbage to me, and I cannot believe that this judge was dumb enough to let this go forward because man, this officially became like a. I can't post this for work in anymore podcast, but whatever. This is one of those deals where

Andrew: 10:25

This is na. Right, right, right. For the record, neither one of us are speaking on behalf of employers, clients or so on. This is a personal podcast and Jason and I are immune to any kind of legislation and blah, blah, blah, blah, blah, and lawsuits. So, okay. Personal opinion.

Jason: 10:42

I wouldn't say that I have immunity for from legislation, but that's okay. That said though sorry, marketing guys, you can't use this one. Here's my problem on this. If we're in and of itself, one, it doesn't build any of the screening questions. So if you have knockout questions that are like. Are you able to lift 50 pounds, which I think is actually reasonable for many jobs, right? Or you have knockout questions like legally able to work in the US or whatever your knockout question might be. They didn't write that question. That question was written by their customer, right? Yeah. That's on them. They facilitate the ability to have knockout questions, by the way, so does everybody else. Every other a TS does this, it's base functionality and in fact, Workday's not particularly good at it. They're not great at this. And if you want them to use their AI to sort and rank and filter your candidates, the best thing to do is to buy the hired score functionality. They acquired Hide Hard Score, which is incredible. It's so good. It is. It has been the best matching technology. On the market for a number of years. I've done a ton of tests with them. I've implemented them a ton and they're good. But the big deal is the first time I heard about white box ai and the the concept of watching the decision chain happen within the ai, all of that. That came from my conversations with hired score. They're the cleanest AI I've ever seen, so. Good luck to these people. They've got no chance whatsoever, and if they buy some total miscarriage of justice happen to win this suit, it'll be 100% because there's a jury involved in this that doesn't understand the technology at all and is so fearful about the risk posed by AI that they punish someone. That is the only way they lose this.

Andrew: 12:43

If you had one person to convince, right? And you had months to do. And for one reason or another, and I've read these briefs and they don't do I, I don't think Workday did a really good job of. Separating out their evolution of assessment versus artificial intelligence during this pan span of time. Yeah. So, right, so, so what? What, unfortunately, for every HR technology company that has gone to a conference this spring, okay. And potentially even last fall. You had the letters A and i next to each other somewhere on your Slack. Right? It's, it was, you were talking about ai. You were doing it because there's a tremendous amount of pressure and private equity pressure, and we gotta retain our people. So that's all over hr. But this Workday case is a lot older than that height. And so well,

Jason: 13:52

The problem that we're gonna run into is that there's so much fear and people are right to be afraid that like their jobs are going to be irrevocably changed. The way that they do work is I mean. How many people are in jobs that are the equivalent of the secretarial pool when the personal computer showed up? Right? Remember back in the day, if you wanted to send a memo out, you would hand it to a secretary who would who he would give, who would take the notes down, then hand it down to a secretarial pool, which is basically a giant computing group of humans that would type up your message and make copies and send it to everyone. That's the way things used to be done. Right. And now, well, everybody is facing the risk of, Hey, I worked in the secretarial pool and there's a machine that can do this thing.

Andrew: 14:45

Yeah. So I, I think a another example of that is if you look in the sixties, okay, so we're going, you know, 65 years ago there was actually the a position called. A computer. What's your title? Computer. Right. That's funny. So, so this is primarily in, you know, science and engineering whether it's Northrop Grumman or NASA or whatever. But you have people who, like, if they have a business card, it would say computer, because their job was to compute mathematical equations,

Jason: 15:20

right? Yeah. Like there's a, there's that movie about the ladies that. Yeah. During the Apollo mission maybe.

Andrew: 15:27

Yeah. No, that was, yeah, that's when they wanted to, that's what they wanted to do, is what they wanted to go and do. Apollo, right? That's right. So, actually that might have been for the Mer that might have been Mercury, but Okay. Yeah, that might, I think, yeah, that was for Mercury. So, maybe, I don't know to look but that's the concept, right? Is you have people who did that and so. So you're right in that the agen press has popped open during this time. Yeah. And part of the, there's a 20, the 20 page the 20 page ruling on collective action that Judge Lynn produced. Part of the plaintiff's case is if you go out there on their website right now, it says that they have all kinds of AI doing all kinds of things, and they've been developing it for a while.

Jason: 16:19

Yeah.

Andrew: 16:20

It's like, well, it's ghost wear. Okay. It's like, well, but you said you had it, so my, so you have, so they did not do a great job, I think workday of putting enough proof in front of the judge to educate on the difference between, okay, someone applies to a job. There's a series of questions. You don't have the ability to work in the country. You don't have proper identification. You do not have a driver's license to debut. You don't have a commercial driver's license. Pick whatever very objective question you could have. And you're right, Jason. It's not workday that comes up with the questions. Yeah, it's the employer. Right. And for one reason or another they didn't call you. And they didn't call me, but I was, I think they, Workday could have called either one of us. And said, can you explain this to

Jason: 17:21

someone because they don't believe us. I'm calling out Jason Sheer, why didn't you call us? Come on. I totally, I could have been you've, I could have been a witness for the defense. I would've been happy to speak on your behalf and to tell these people that this is total nonsense. Come on, man. It's absolutely, aren't you in charge of that strategy now?

Andrew: 17:41

Yeah. I don't understand what, like, you would've thought that if Theta and Jason would've called both of us and be like can you like call someone for there? But it, it did strike me that Workday. Workday did the industry a bit of a disservice. I don't know what goes on behind the scenes, but I would've advised Workday to probably go grab a handful of other applicant tracking systems and come up with a storyline that would've been very solid. And this way, because now what's happened is the door's been opened. I don't care if your workday, and look, I have no allegiance to anybody. Workday, ims, smart recruiters, Oracle, on and on. Go. Go find some list that's, you know, go to talent tech labs and go download that entire list of anybody who applies through any application system. And now they're all like, what do we do now? They're all waiting because now that this has gone to collective action. Even though we're not even in a position where we know how many plaintiffs there could be the fact that, oh, you have AI ish applications, and and you've been talking about it for a while, and I haven't gotten a hired. I mean, I don't know why someone just doesn't go ahead and go through all their emails and see how many times smart recruiters and iCIMS came up and give them a call at iCIMS and Red Bank and go ahead and file in my district here for federal court. You probably could.

Jason: 19:21

So the big winner in this, so say the plaintiff's win, say that class gets gathered. And the plaintiffs ultimately win in this action, right? Who are the big winners and the big losers in that deal? Oh,

Andrew: 19:37

I can't wait to be the first solopreneur who is like a billionaire. I.

Jason: 19:41

Well, I agree with that but here's my, yeah, I guess the guy that, that certifies everyone's AI audits, he might get busy. Hey if you're an HR tech and you haven't done your AI audit, you probably ought to pick up the phone guys. That's,

Andrew: 19:55

yeah.

Jason: 19:55

You better get somebody in there. You know? That's true. Okay. Yeah. You're sitting on your gold mine. Here's what I was thinking. I was thinking. Outside of the people on this on this call, that's right. So even if they lose big, but they lost big in a class action suit. Right. We've had class action suits where there are massive losers like in the tobacco companies, for example, that this happened for. Right. So. What ends up happening? I think the biggest loser is probably the Masters because they take the money they spend on a tiny fraction of their marketing, like sponsoring the Masters or whatever, and Workday pays the plaintiffs whatever they happen to win and then go on about their business. So in fact, it's the masters who loses when this is all said and done. We're gonna have to have a new sponsor for golf. That's my guess. The the PGA will get hosed the other, the winners in this, if we see a big win out of this and massive payout from Workday, by the way, again, I don't think this is gonna happen. I think it's a silly lawsuit that has very little merit whatsoever, and they've chosen to sue someone who's not responsible for what's going on in their world. I. That being said you never know. So if Workday were to lose, I think recruiters are the big winners in this. Oh, they're

Andrew: 21:18

huge.

Jason: 21:19

It has

Andrew: 21:19

saved their job.

Jason: 21:21

Yeah.

Andrew: 21:21

All because now you need to have human decision. That's right. And you have to prove the human decision. And I'll tell you who some of the losers are. Some of the losers let's call it the a let's call them agents. Okay. Okay. They're, I think one of the losers is the applicant to interview transaction inside the a TS, having any kind of automation to it. Oh yeah. So there has to be like a place. This stinks because you and I have seen, I don't know how many systems where recruiters are incapable of saying, I reviewed this person and then I change their stage. Right. It's almost like if you could actually manually do that and make sure that it's never automated, you would have some sort of a trail that says there was a human intervention somewhere. Right. Or, you know, okay, someone's in application hasn't been reviewed and you've done this and you and I have done this together. Someone's application hasn't been reviewed in so many days. It has to be escalated and been reviewed by somebody. Right? Yeah. Right. So those types of things can all get done. But you're right, I think whether they're. I don't know if there's, you know, let's call them recruiters for right now, but individual contributors who have to look at a applicant and make a human decision. And that could be hiring managers, by the way. And they're the winners in this where the work that they thought was gonna go away may not be going away at the rate they thought.

Jason: 23:03

Yeah. No I agree. When, you know, here's the thing, CLO, which is my day job, where I'm not a Intrepid podcast host a a semi-annual podcast host. We're automating a ton of stuff in the recruiting process, like a ton of stuff in the recruiting process and, we're certainly gonna be paying attention. We're gonna watch. Now none of our stuff is about making decisions. It's about streamlining the process and empowering recruiters with more stuff, right? So we don't have any decision making stuff and there is a different level of risk there, but it's it's definitely something that to pay attention to. Here's a question since I have the the AI expert on the AI legislation expert on the call. Here we go. Alright. So, for my own personal thing outside of my day job, I just launched Better Thing ai, right? So Better thing.ai. Yep. And it's the flip of this. It's helping candidates automatically, find jobs that match their resume, and then automating the customization of their resume outreach to their network. All the stuff that you need to do when you're searching for jobs. It's so hard right now. Like 0.5% of applicants are hired today, which means it's one out of every 200. Imagine submitting 200 applications to get hired. It's crazy. So it's simply a tool that helps enable candidates to do that in a more automated, easier way. Right. That's all it does. Yeah. What are the risks associated with that, given the AI legislation?

Andrew: 24:36

Well, so I. So the first, I think the first thing is the deployer, which is you, right? Yeah. There's nothing company associated

Jason: 24:45

with this is like a Jason's Ventures.

Andrew: 24:48

Jason.

Jason: 24:48

Jason's ventures, LLC, Jason's Ventures, LLC. If only there were, I'll see. Maybe I should get on that.

Andrew: 24:55

So if a developer. Is using some sort of machine learning automation something that would then translate into an output they have to expose, you know, how are you doing that? And so in some cases it might be, well, we're, you know, we're using this statistical model for advancement or this statistical model for transformation, or in your case it's, well, I went ahead and. I found a job for you based on your skillset using similarity matching, right? Probably the case. Yeah. And then I went ahead. I simply

Jason: 25:31

bt write the

Andrew: 25:32

right search, I'm gonna go ahead, use open AI to, you know, alter your, you know, to look at the position and if someone wants to go ahead and use that information to alter their resume. Provided that they provided that the buyer. Has off has said, I'm approving this. Right then. And if you've disclosed how it gets done and they say yes, then you're okay. It's no different than them doing chat GPT for themselves, and it's really no different than indeed sending off an alert. Yeah, you've just made it a little bit easier, but they have to go ahead and still hit the button on. I believe that this represents me, and those kinds of things. And then there, and as long as you've disclosed, you're fine. Where that becomes a little dicey is if the is, you know, you'd have to have some sort of level of liability that you're, you know, you're immune to it, saying, look, I'm not gonna tell you that because I Go ahead. And change your resume if you don't check it and you misrepresent yourself.

Jason: 26:41

Yeah, that's a big one. And then you find

Andrew: 26:42

out later, I'm mean, you. Right, right. You know, that's, and that's the thing. So when a candidate, when a person of interest looks at a job, it is their responsibility to whatever data that they go ahead and provide to that company. They are saying that represents me correctly. Yeah,

Jason: 27:03

that's Well, and they're the ones that have to check that box, right? So they have to check the box. It's not you, they gotta check the box. That's right. That's true. Right. So I guess that's, that risk does not float over to me, though. They could complain or accuse me of it. It would be difficult for someone to raise a suit. All right. Well, chalk that up to the solopreneur. Not billionaire. Thanks for. Thanks for the help. Put it this way. Future brain.

Andrew: 27:27

Yeah. Put it this way. Let's just say that you've got 10 versions of a resume. Right. So you're a data you're like us, right? You know, it's like we could probably do like seven different things. So let's just say we have, so if I have a workforce plan, a strategic workforce planning resume versus an artificial intelligence and pay equity auditing resume, right? Yeah. Clearly can do both, right? Given the background and, but maybe you move your words around. So you have version one and version two. If I accidentally put version one into a job as I respond to an application, but I put in version two instead of version one, that's on me. Yeah. Right. Yeah. That's on me. So if you are finding jobs that are coming to you automated and you upload the wrong data because you, you gave a tool permission to do so and you didn't check, well, that's still. Applicant's fault. Right. True enough. And yeah, true enough.

28:27

We,

Andrew: 28:28

yeah. Yeah. So, so you're cool. But on the other side is, you know, when you're going back to this workday thing, I mean, you know, if you're the employer now, you're worried about. You are worried about all kinds of things related to the automated employment decision tools that you're having because number one, you have your tool, you, so you have your tool running and now people are applying to 200 jobs in a day, right? So there's a whole other dialogue around over throttling the jobs. I put in this article that went out on a mobilely workday, and what Workday should do is what is Workday gonna do when the cybersecurity implications alone associated with reaching out to a billion people and knowing that it's public. Can you imagine people who have applied to jobs getting a notification from a spoofed workday address?

Jason: 29:27

Oh, yeah. Well, and that's, oh

29:28

my God.

Jason: 29:30

Oh man, that's a scammer paradise right there. It's

29:33

a dream.

Jason: 29:34

It's a, oh my

29:35

gosh. I mean, that's one of the points I made is I'm like a billion

Andrew: 29:40

submissions. Everybody and their, you know, everybody and their children are going to get a notification. And if I was workday, get one, that's what I would've led. I'm gonna get

Jason: 29:51

one. During the time of this thing that was back, I think this is over two years

Andrew: 29:56

old now. It's gonna be for all the way back to 2020, September of 2020. So by the time they figure out probably how to do this. Right. And they said from present from, so the, so, so by the time they figure this out, and here we are. Memorial Day. Let's say they figure it out by September 24th, 2025. It's five full years of submissions.

Jason: 30:26

Yeah, I think my formal application to Accenture the last time I went to work for them will be in there. I. And I think that when I left JP Morgan and I was looking for stuff, surely I, I talked to somebody at a workday shop. I dunno who, yeah. But I think I only considered like three different companies. I was ready to like buy a car wash and get out the business at the time.

Andrew: 30:49

I'm gonna, I'm gonna get some from my own customers because we always do the mystery applicant thing.

Jason: 30:56

Oh my gosh, I just did 200 mystery applications. I'm gonna get hundreds of these. I forgot about that.

31:02

Why?

Jason: 31:03

I applied to 200 jobs.

31:05

I mean, Jerry Crispin might get 80,000.

Jason: 31:07

Oh my gosh. He's Mr.

31:09

He's like Mr. Mystery applicant.

Jason: 31:11

Yeah. So I decided I did this thing. I'll eventually do a video on this. I've got the stats compiled now, but, I applied, I was like, well, if it's one out of 200 that gets hired, I'm gonna apply 200 times and see what happens. So I compiled the stats on how often I got a call back and how often I was offered an interview. Now I didn't do any interviews. I didn't go that far because the other thing I was doing is I was applying with perfect resumes. So the. The better thing, ai, it will do a, it will match the verbiage of a resume and it'll tell you up front like it's a 78% match and I got you to a 90 or 95, 90 8%, whatever that got you to, so what I did was for several software engineer jobs, I I had chat GPT create a dummy resume for me, just a raw dummy resume. Then for each of the individual jobs, I customized that resume for that job. So it was a perfect resume for a perfect fit job is what I ended up applying for 200 times because I wanted to see not only how often do you get responses, but how often when you're a fit for the job do you get responses. Right. Right. It's not as much as you would think. It's like less than 10%.

Andrew: 32:31

Oh, it's crazy. It's, you know, it's, I do believe that some of the takeaways, let's talk about the takeaways people should take from this case, right? Number one, so you talked about the winners and the losers. So the winners are the recruiters who, okay. You asked the question who we who are the losers?

Jason: 32:48

Yep.

Andrew: 32:48

Right. So I think that we've got a handful of losers. Is probably the Human Capital Management human Capital Management systems. Yeah. Right. Because this case can be used not just for applications, but for anything around automated decisions. So yeah. Okay. Yeah. You applied and you assessed, but you were discriminated against. Okay. So. This case could be whipped around and saying, you didn't promote me. You didn't give me the learning. You didn't approve my education. You didn't give me more pay, and I worked for you, and you've got AI running around. I. Right. So realize this could be turned not just to applicant tracking tools. This can get potentially turned into, I just work at a company and I wanna make sure that the human capital management system that's paying me and doing my learning and everything else isn't discriminating against me because it's got AI floating in there. So I think HCM tools, even if you're not hiring anybody. Okay. They're a little bit of a loser because, okay, they need to make sure that their ship is tight. Then I think that there's the applicant tracking systems and the CRM systems, and I'm saying them separately because. People who go ahead and say, Hey, I'm an applicant, and then someone's gonna get reviewed by ai or an assessment at a company is one thing, but if you're going out into the market and looking for candidates and you're using the CRM tool, a sourcing tool, you're using branding tools to automatically post jobs in certain places. And, you know, you're dis you could be discriminating that way. Yeah. And this case could run there. So I think that we've got some tech losers out there, but they can all get tightened up. They can get tightened up and, you know, and say no. Here's our black box. We don't have a black box. It's all open and you know, here it is. And everything's cool. I just think that we're just behind. I think everyone was hoping this was gonna go away and this has not gone away.

Jason: 35:13

Any other HR tech that should be worried is probably paradox. cause they do that high volume business. Yep. And they've got so many applicants pump pumping through there in so many different companies. And they are making decisions, right? They, part of the deal is people do the screening questions over text. And how hard is it to prove qualified or not qualified on those high volume, low? Low qualification jobs.

Andrew: 35:40

Our friend Adam is probably, he is not Adam. Get the smelling sauce. Get the smell salt,

Jason: 35:45

he'll be fine. Oh my God. That's funny. I think they'll make it over paradox,

35:50

Well, we will wrap up Mobley versus Workday, right there. Thank you so much for joining the Recruiting Technology podcast. Remember to follow and subscribe depending on where you're listening to this podcast. And you'll hear about the next one as soon as it comes out. Adios.